Biology subjects

Blum, Y.

Publications and source records attributed to Blum, Y..

16 recordsLinked to original sources

bioRxiv2026

The constitutive androstane receptor protects against metabolic dysfunction-associated steatotic liver disease through sex specific interactions with the gut microbiota

Background: The gut-liver axis is involved in Metabolic dysfunction-Associated Steatotic Liver Disease (MASLD), but the host molecular actors involved in such dialogue have not yet been fully characterized. Objective: We investigated the sex-dependent role of the Constitutive Androstane Receptor (CAR) as a hepatic sensor of microbial signals in MASLD pathophysiology. Design: Male and female Car+/+ and Car-/- mice were fed a western diet (WD) for 4, 14 or 35 weeks. We performed plasma biochemistry, liver histology, bile acid and cholesterol quantification, untargeted multi-omics approach combining liver RNA-sequencing and 16S rRNA sequencing, together with co-housing, fecal microbiota transplantation and analysis of publicly available transcriptomics data in human cohorts. Results: Short-term WD revealed CAR-dependent protection against steatosis, together with perturbations in the transcriptional signatures of multiple transcription factors involved in hepatocyte identity in males. After 14 weeks, CAR deletion increased WD-induced liver damage, inflammation and fibrosis, and disrupted bile acid, cholesterol and gut microbiota homeostasis, in males only. Co-housing and fecal microbiota transplantations revealed that a Car+/+ gut microbiota protected against WD-induced liver damage, while a Car-/- microbiota was reshaped by a Car+/+ host. No CAR-dependent phenotype was observed in females. Finally, in human cohorts, hepatic CAR expression decreased in advanced clinical stages of MASLD. Conclusion: CAR is a sex-dependent protective nuclear receptor against MASLD progression, acting both as a transcriptional regulator of hepatocyte identity and as a mediator of the host-microbiota crosstalk.

physiology↗

bioRxiv2026

A single-nucleus atlas of the adult laying hen liver reveals metabolic specialization and improved cellular resolution through enhanced genome annotation

The liver of laying hens plays a central role in metabolism and reproduction, supporting the synthesis of egg yolk precursors under strong hormonal regulation. Despite its physiological importance, a high-resolution cellular reference of the adult chicken liver is still lacking. Here, we generated a single-nucleus RNA sequencing atlas of the adult laying hen liver from eight individuals, providing a comprehensive view of its cellular composition and transcriptional landscape. Using this framework, we identified major hepatic cell populations, including hepatocytes, endothelial cells, cholangiocytes, hepatic stellate cells, and diverse immune cell types, revealing a broadly conserved vertebrate liver architecture. However, hepatocyte zonation, a key feature of mammalian liver organization, was not observed, consistent with the absence of hepatocyte zonation reported in birds. Importantly, we demonstrate that the use of an enriched genome annotation, incorporating additional protein-coding and long non-coding RNA models, substantially improves transcript detection and enhances cell-type resolution in single-nucleus datasets. This improved resolution allows more accurate marker-based assignment of hepatocyte subpopulations and refines the interpretation of hepatic cellular heterogeneity. Within hepatocytes, we uncovered transcriptionally distinct subpopulations associated with lipid metabolism and reproductive function, including estrogen-responsive programs involving cytochrome P450 genes such as CYP2C23A and CYP2C23B. In parallel, we characterized a complex immune compartment composed of resident macrophages and adaptive immune cells, highlighting the dual metabolic and immunological roles of the avian liver. Overall, this atlas provides a high-resolution reference for avian liver biology and demonstrates that improved genome annotation enhances the resolution and interpretation of cellular heterogeneity in single-cell transcriptomic studies.

genomics↗

bioRxiv2025

Hepatocyte ERα orchestrates sex-specific liver adaptation to fasting and feeding states

Sex differences in hepatic physiology are thought to influence individual susceptibility to chronic liver diseases including Metabolic-Associated Steatotic Liver Disease (MALSD). Previous studies demonstrated the central contribution of estrogens which primarily influence liver biology through the activation of Estrogen Receptor alpha (ER). However, how ER signaling in hepatocyte modulates liver functions according to the nutritional status, a critical determinant of hepatic metabolism, remains to be characterized. The present study first reveals the nycthemeral expression profile of liver ER, which peaks during the feeding period (ZT16) in both male and female mice. ER expression is altered by reprogramming the hepatic circadian clock in response to inverted food intake, highlighting the influence of feeding on liver ER expression patterns. As ER is mainly expressed in hepatocytes both in human and mouse livers, the functional role of hepatocyte ER during fasting or feeding state was then delineated, using mice harboring ER hepatocyte-specific deletion (ERhep-/-) compared with their wild-type littermates (ERhep+/+). Transcriptomic analyses reveal significant sex differences in the adaptation of liver functions to this contrasted nutritional status, as well as the sex-specific regulatory effects of hepatocyte ER. In such physiological settings, hepatocyte ER deletion does not influence liver transcriptomic profiles in males but significantly alters gene expression in female livers, both fed and fasted conditions. Hepatocyte ER more specifically controls genes associated with inflammatory responses and fatty acid metabolic pathways in females, modulating the ChREBP and PPAR pathways in feeding or fasting states, respectively. Thus, hepatocyte ER is integral to liver metabolic adaptations to fasting and feeding in females but not in males, thus exhibiting both sex-specific and diet-dependent actions. Further characterizing sex differences in liver metabolic flexibility, these results provide new information to develop sex-based strategies for the prevention and management of MASLD.

physiology↗

bioRxiv2025

Benchmarking circRNA Detection Tools from Long-Read Sequencing Using Data-Driven and Flexible Simulation Framework

AO_SCPLOWBSTRACTC_SCPLOWCircular RNAs (circRNAs) are unique non-coding RNAs with covalently closed loop structures formed through backsplicing events. Their stability, tissue-specific expression patterns, and potential as disease biomarkers have garnered increasing attention. However, their circular structure and diverse size range pose challenges for conventional sequencing technologies. Long-read Oxford Nanopore (ONT) sequencing offers promising capabilities for capturing entire circRNA molecules without fragmentation, yet the effectiveness of bioinformatic tools for analyzing this data remains understudied. This study presents the first comprehensive benchmark comparison of three specialized tools for circRNA detection from ONT long-read data: CIRI-long (Zhang et al., 2021), IsoCIRC (Xin et al., 2021), and circNICK-Irs (Rahimi et al., 2021). To address the lack of standardized evaluation frameworks, we developed a novel computational pipeline, open-source and freely available, to generate realistic simulated circRNA ONT long-read datasets. Our pipeline integrates several molecular features of circRNAs extracted from established databases and real datasets into NanoSim tool (Hafezqorani et al., 2020) and outputs FASTQ reads reflecting therefore biological diversity and technical properties. We systematically assessed tool performance across key metrics, including precision, recall, specificity, accuracy, and F1 score. Our analysis revealed distinct performance profiles: while all tools exhibited high specificity, they varied in precision and their ability to detect different circRNA subtypes, often showing limited sensitivity and precision. Notably, the overlap in detected circRNAs among tools was relatively low. Additionally, computational efficiency varied significantly across the tools. This suggests that relying on a single tool might not be ideal, and combining tools or improving algorithms could be necessary for more accurate circRNA detection from ONT data. This benchmark provides valuable insights for researchers selecting appropriate tools for circRNA studies using ONT sequencing. Furthermore, our customizable simulation framework, offering a resource to optimize detection approaches and advance bioinformatic tool development for circRNA research is freely available at: https://gitlab.com/bioinfog/circall/nano-circ.

bioinformatics↗

bioRxiv2025

Teach your microscope how to print: Low-cost and rapid-iteration microfabrication for biology

The application of traditional microfabrication techniques to biological research is hindered by their reliance on clean rooms, expensive or toxic materials, and slow iteration cycles. We present an accessible microfabrication workflow that addresses these challenges by integrating consumer 3D printing techniques and repurposing standard fluorescence microscopes equipped with DMDs for maskless photolithography. Our method achieves micrometer-scale precision across centimeter-sized areas without clean room infrastructure, using affordable and readily available consumables. We demonstrate the versatility of this approach through four biological applications: inducing cytoskeletal protrusions via 1 m-resolution surface topographies; micropatterning to standardize cell and tissue morphology; fabricating multilayer microfluidic devices for confined cell migration studies; imprinting agar chambers for long-time tracking of C. elegans. Our protocol drastically reduces material costs compared to conventional methods and enables design-to-device turnaround within a day. By leveraging open-source microscope control software and existing lab equipment, our workflow lowers the entry barrier to micro-fabrication, enabling labs to prototype custom solutions for diverse experimental needs while maintaining compatibility with soft lithography and downstream biological assays.

cell biology↗

bioRxiv2024

A robust workflow to benchmark deconvolution of multi-omic data

Tumour heterogeneity significantly affects cancer progression and therapeutic response, yet quantifying it from bulk molecular data remains challenging. Deconvolution algorithms, which estimate cell-type proportions in bulk samples, offer a potential solution. However, there is no consensus on the optimal algorithm for transcriptomic or methylomic data. Here, we present an unbiased evaluation framework for the first comprehensive comparison of deconvolution algorithms across both omic types, including reference-based and -free approaches. Our evaluation covers raw performance, stability, and computational efficiency under varying conditions, such as missing or additional cell types and diverse sample compositions. We apply this framework across multiple benchmark datasets, including a novel multi-omics dataset generated specifically for this study. To ensure transparency and re-usability, we have designed a reproducible work-flow using containerization and publicly available code. Our results highlight the strengths and limitations of various algorithms, and provides practical guidance for selecting the best method based on data type and analysis context. This benchmark sets a new standard for evaluating deconvolution methods and analysing tumour heterogeneity.

bioinformatics↗

bioRxiv2024

p110α-dependent hepatocyte signaling is critical for liver gene expression and its rewiring in MASLD

Insulin and other growth factors are key regulators of liver gene expression, including in metabolic diseases. Most of the phosphoinositide 3-kinase (PI3K) activity induced by insulin is dependent on PI3K. We used mice lacking p110, the catalytic subunit of PI3K, to investigate its role in the regulation of liver gene expression in health and in Metabolic dysfunction-Associated Steatotic Liver Disease (MASLD). The absence of hepatocyte PI3K signaling promoted glucose intolerance in lean mice and significantly regulated liver gene expression, including insulin-sensitive genes, in ad libitum feeding. Some of the defective regulation of gene expression in response to hepatocyte-restricted insulin receptor deletion was related to PI3K signaling. In addition, though PI3K deletion in hepatocytes promoted insulin resistance, it was protective against steatotic liver disease in diet-induced obesity. In the absence of hepatocyte PI3K, the effect of diet-induced obesity on liver gene expression was significantly altered, with changes in rhythmic gene expression in liver. Altogether, this study highlights the specific role of p110 in the control of liver gene expression in physiology and in the metabolic rewiring that occurs during MASLD.

cell biology↗

bioRxiv2023

Redefining phenotypic intratumor heterogeneity of pancreatic ductal adenocarcinoma: a bottom-up approach

BackgroundPancreatic ductal adenocarcinoma (PDAC) tumor inter-patient heterogeneity has been well described with two major prognostic subtypes (classical and basal-like). An important intra-patient heterogeneity has been reported but has not yet been extensively studied due to the lack of standardized, reproducible and easily accessible high throughput methods. Material and MethodsWe built an immunohistochemical (IHC) tool capable of differentiating RNA-defined classical and basal-like tumors by selecting relevant antibodies using a multi-step process. The successive stages of i) an in-silico selection from a review literature and a bulk transcriptome analysis of 309 PDACs, ii) a tumor-specific selection from 30 patient-derived xenografts followed by iii) the validation on tissue microarrays in 50 PDAC were conducted. We used our final IHC panel on two independent cohorts of resected PDAC (n=95, whole-slide, n=148, tissue microarrays) for external validation. After digitization and registration of pathology slides, we performed a tile-based-analysis in tumor and pre-neoplastic epithelial areas and a k-means clustering to identify relevant marker combinations. ResultsSequential marker selection led to the following panel: GATA6, CLDN18, TFF1, MUC16, S100A2, KRT17, PanBasal. Four different phenotypes were identified: 1 classical, 1 intermediate (KRT17+) and 2 basal-like (MUC16+ vs S100A2+) with specific biological properties. The presence of a minor basal contingent drastically reduced overall survival, even in classical predominant PDACs (HR=2.36, p=0.01). Analysis of preneoplastic lesions suggested that pancreatic carcinogenesis may follow a progressive evolution from classical toward a basal through an early intermediate phenotype. ConclusionOur IHC panel redefined and easily assessed the high degree of intra- and inter-tumoral heterogeneity of PDAC.

cancer biology↗

bioRxiv2023

Cirscan: a shiny application to identify differentially active sponge mechanisms and visualize circRNA-miRNA-mRNA networks.

BackgroundNon-coding RNAs represent a large part of the human transcriptome and have been shown to play an important role in disease such as cancer. However, their biological functions are still incompletely understood. Among noncoding RNAs, circular RNAs (circRNAs) have recently been identified for their microRNA (miRNA) sponge function which allows them to modulate the expression of miRNA target genes by taking on the role of competitive endogenous RNAs (ce-circRNAs). Today, most computational tools are not adapted to the search for ce-circRNAs or have not been developed for the search for ce-circRNAs from users transcriptomic data. ResultsIn this study, we present Cirscan (CIRcular RNA Sponge CANdidates), an interactive Shiny application that automatically infers circRNA-miRNA-mRNA networks from human multi-level transcript expression data from two biological conditions (e.g. tumor versus normal conditions in the case of cancer study) in order to identify on a large scale, potential sponge mechanisms active in a specific condition. Cirscan ranks each circRNA-miRNA-mRNA subnetwork according to a sponge score that integrates multiple criteria based on interaction reliability and expression level. Finally, the top ranked sponge mechanisms can be visualized as networks and an enrichment analysis is performed to help its biological interpretation. We showed on two real case studies that Cirscan is capable of retrieving sponge mechanisms previously described, as well as identifying potential novel circRNA sponge candidates. ConclusionsCirscan can be considered as a companion tool for biologists, facilitating their ability to prioritize sponge mechanisms for experimental validations and identifying potential therapeutic targets. Cirscan is implemented in R, released under the license GPL-3 and accessible on GitLab (https://gitlab.com/geobioinfo/cirscan_Rshiny). The scripts used in this paper are also provided on Gitlab (https://gitlab.com/geobioinfo/cirscan_paper).

bioinformatics↗

bioRxiv2022

Preclinical evaluation of CDK4 phosphorylation predicts high sensitivity of malignant pleural mesotheliomas to CDK4/6 inhibition

Malignant pleural mesothelioma (MPM) is an aggressive cancer with limited therapeutic options. In this study, we evaluated the impact of CDK4/6 inhibition by palbociclib in a panel of 28 MPM cell lines, including 19 patient-derived cell lines, using a variety of approaches including RNA-sequencing. Palbociclib used alone sufficed to strongly and durably inhibit the proliferation of 23 MPM cell lines, indicating a unique sensitivity of MPM to CDK4/6 inhibition. Importantly, insensitivity to palbociclib was mostly explained by the lack of active T172-phosphorylated CDK4. This was associated with the high p16INK4A (CDKN2A) levels that accompany RB1 defects or inactivation, and also (unexpectedly) cyclin E1 over-expression in the presence of wild-type RB1. Prolonged treatment with palbociclib irreversibly inhibited proliferation despite re-induction of cell cycle genes upon drug washout. A senescence-associated secretory phenotype including various potentially immunogenic components was also irreversibly induced. Phosphorylated CDK4 was detected in 80% of 47 MPM tumors indicating their intrinsic sensitivity to CDK4/6 inhibitors. The absence of this phosphorylation in some highly proliferative MPM tumors was linked to partial deletions of RB1, leading to very high p16 (CDKN2A) expression. Our study strongly supports the clinical evaluation of CDK4/6 inhibitory drugs for MPM treatment, in monotherapy or combination therapy.

cancer biology↗

bioRxiv2022

Crest maturation at the cardiomyocyte surface contributes to a new late postnatal development stage that controls the diastolic function of the adult heart

RATIONALEIn addition to its typical rod-shape, the mammalian adult cardiomyocyte (CM) harbors a unique lateral membrane surface architecture with periodic crests, relying on the presence of subsarcolemmal mitochondria (SSM) the role of which is still unknown. OBJECTIVETo investigate the development and functional role of CM crests during the postnatal period. METHODS AND RESULTSElectron/confocal microscopy and western-blot of left ventricular tissues from rat hearts indicated a late CM surface crest maturation, between postnatal day 20 (P20) and P60, as shown by substantial SSM swelling and increased claudin-5 cell surface expression. The P20-P60 postnatal stage also correlates with an ultimate maturation of the T-Tubules and the intercalated disk. At the cellular level, we identified an atypical CM hypertrophy characterized by an increase in long- and short-axes without myofibril addition and with sarcomere lateral stretching, indicative of lateral stretch-based CM hypertrophy. We confirmed the P20-P60 hypertrophy at the organ level by echocardiography but also demonstrated a transcriptomic program after P20 targeting all the cardiac cell populations. At the functional level, using Doppler echocardiography, we found that the P20-P60 period is specifically dedicated to the improvement of relaxation. Mechanistically, using CM-specific knock-out mice, we identified ephrin-B1 as a determinant of CM crest maturation after P20 controlling lateral CM stretch-hypertrophy and relaxation. Interestingly, while young adult Efnb1CMspe-/- mice essentially show a relaxation impairment with exercise intolerance, they progressively switch toward heart failure with 100% KO mice dying after 13 months. CONCLUSIONSThis study highlights a new late P20-P60 postnatal developmental stage of the heart in rodents during which the CM surface crests mature through an ephrin-B1-dependant mechanism and regulate the diastolic function. Moreover, we demonstrate for the first time that the CM crest architecture is cardioprotective.

cell biology↗

bioRxiv2022

PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides

Pancreatic ductal adenocarcinoma (PAC) is a highly heterogeneous and plastic tumor with different transcriptomic molecular subtypes that hold great prognostic and theranostic values. We developed PACpAInt, a multistep approach using deep learning models to determine tumor cell type and their molecular phenotype on routine histological preparation at a resolution enabling to decipher complete intratumor heterogeneity on a massive scale never achieved before. PACpAInt effectively identified molecular subtypes at the slide level in three validation cohorts and had an independent prognostic value. It identified an interslide heterogeneity within a case in 39% of tumors that impacted survival. Diving at the cell level, PACpAInt identified "pure" classical and basal-like main subtypes as well as an intermediary phenotype and hybrid tumors that co-carried both classical and basal-like phenotypes. These novel artificial intelligence-based subtypes, together with the proportion of basal-like cells within a tumor had a strong prognostic impact.

cancer biology↗

bioRxiv2020

DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification

MotivationQuantification of tumor heterogeneity is essential to better understand cancer progressionand to adapt therapeutic treatments to patient specificities. ResultsWe present DECONbench, a web-based application to benchmark computational methods dedicated to quantify of cell-type heterogeneity in cancer. DECONbench includes benchmark datasets, computational methods and performance evaluation. It allows submission of new methods. Availability and implementationDECONbench is hosted on the open source codalab competition platform. It is freely available at: https://competitions.codalab.org/competitions/23660. Supplementary informationAdditional information is available online and on our website: https://cancer-heterogeneity.github.io/deconbench.html.

bioinformatics↗

bioRxiv2020

Establishment of a pancreatic adenocarcinoma molecular gradient (PAMG) that predicts the clinical outcome of pancreatic cancer

BACKGROUNDA significant gap in pancreatic ductal adenocarcinoma (PDAC) patients care is the lack of molecular parameters characterizing tumors and allowing a personalized treatment. The goal of this study was to examine whole PDAC transcriptomic profiles to define a signature that would predict aggressiveness and treatment responsiveness better than done until now. METHODS AND PATIENTSTumors were obtained from 76 consecutive resectable (n=40) or unresectable (n=36) tumors. PDAC were transplanted in mice to produce patient-drived xenografts (PDX). PDX were classified according to their histology into five groups, from highly undifferentiated to well differentiated. This classification resulted strongly associated with tumors aggressiveness. A PDAC molecular gradient (PAMG) was constructed from PDX transcriptomes recapitulating the five histological groups along a continuous gradient. The prognostic and predictive value for PMAG was evaluated in: i/ two independent series (n=598) of resected tumors; ii/ 60 advanced tumors obtained by diagnostic EUS-guided biopsy needle flushing and iii/ on 28 biopsies from mFOLFIRINOX treated metastatic tumors. RESULTSA unique transcriptomic signature (PAGM) was generated with significant and independent prognostic value. PAMG significantly improves the characterization of PDAC heterogeneity compared to non-overlapping classifications as validated in 4 independent series of tumors (e.g. 308 consecutive resected PDAC, HR=0.321 95% CI [0.207;0.5] and 60 locally-advanced or metastatic PDAC, HR=0.308 95% CI [0.113;0.836]). The PAMG signature is also associated with progression under mFOLFIRINOX treatment (Pearson correlation to tumor response: -0.67, p-value < 0.001). CONCLUSIONWe identified a transcriptomic signature (PAMG) that, unlike all other stratification schemas already proposed, classifies PDAC along a continuous gradient. It can be performed on formalin-fixed paraffin-embedded samples and EUS-guided biopsies showing a strong prognostic value and predicting mFOLFIRINOX responsiveness. We think that PAMG could unify all PDAC preexisting classifications inducing a shift in the actual paradigm of binary classifications towards a better characterization in a gradient. Trial RegistrationThe PaCaOmics study is registered at www.clinicaltrials.gov with registration number NCT01692873. The validation BACAP study is registered at www.clinicaltrials.gov with registration number NCT02818829.

cancer biology↗

bioRxiv2019

Temporal perturbation of Erk dynamics reveals network architecture of FGF2-MAPK signaling

Stimulation of PC-12 cells with epidermal (EGF) versus nerve (NGF) growth factors (GFs) biases the distribution between transient and sustained single-cell ERK activity states, and between proliferation and differentiation fates within a cell population. We report that fibroblast GF (FGF2) evokes a distinct behavior that consists of a gradually changing population distribution of transient/sustained ERK signaling states in response to increasing inputs in a dose response. Temporally-controlled GF perturbations of MAPK signaling dynamics applied using microfluidics reveals that this wider mix of ERK states emerges through the combination of an intracellular feedback, and competition of FGF2 binding to FGF receptors (FGFR) and heparan-sulfate proteoglycans (HSPGs) co-receptors. We show that the latter experimental modality is instructive for model selection using a Bayesian parameter inference. Our results provide novel insights into how different receptor tyrosine kinase (RTK) systems differentially wire the MAPK network to fine tune fate decisions at the cell population-level.\n\nMicrofluidics, Erk Signaling Dynamics, Mechanistic Modelling, Parameter Estimation, Cell Fate Determination

systems biology↗

bioRxiv2018

SMAP: exploiting high-throughput sequencing data of patient derived xenografts

BackgroundPatient-derived xenograft is the model of reference in oncology fordrug response analyses. Xenografts samples have the specificity to be composedof cells from both the graft and the host species. Sequencing analysis ofxenograft samples therefore requires specific processing methods to properlyreconstruct genomic profiles of both the host and graft compartments.\n\nResultsWe propose a novel xenograft sequencing process pipeline termedSMAP for Simultaneous mapping. SMAP integrates the distinction of host andgraft sequencing reads to the mapping process by simultaneously aligning to bothgenome references. We show that SMAP increases accuracy of species-assignmentwhile reducing the number of discarded ambiguous reads compared to otherexisting methods. Moreover, SMAP includes a module called SMAP-fuz toimprove the detection of chimeric transcript fusion in xenograft RNAseq data. Finally, we apply SMAP on a real dataset and show the relevance of pathway andcell population analysis of the tumoral and stromal compartments.\n\nConclusionsIn high-throughput sequencing analysis of xenografts, our resultsshow that: i. the use of ad hoc sequence processing methods is essential, ii. highsequence homology does not introduce a significant bias when proper methodsare used and iii. the detection of fusion transcripts can be improved using ourapproach. SMAP is available on GitHub: cit-bioinfo.github.io/SMAP.

genomics↗